AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Potassium channel subfamily K member 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for ion channels.

 Fig. 1. The sreening workflow of Receptor.AI

This includes extensive molecular simulations of the ion channel in its native membrane environment, in open, closed, and inactivated forms, paired with ensemble virtual screening that factors in conformational mobility in each state. Tentative binding pockets are considered in the pore, the gating region, and allosteric areas to capture the full range of mechanisms of action.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

O14649

UPID:

KCNK3_HUMAN

Alternative names:

Acid-sensitive potassium channel protein TASK-1; TWIK-related acid-sensitive K(+) channel 1; Two pore potassium channel KT3.1

Alternative UPACC:

O14649; Q53SU2

Background:

Potassium channel subfamily K member 3, also known as TASK-1, plays a pivotal role in cellular function by regulating potassium ion flow. This pH-dependent, voltage-insensitive channel facilitates background potassium current, crucial for maintaining cellular membrane potential. Its activity varies with external potassium concentration, acting as an outward rectifier under low concentrations and inward under high.

Therapeutic significance:

TASK-1's involvement in Pulmonary hypertension, primary, 4, a rare but fatal disease, underscores its therapeutic potential. Understanding TASK-1's function and regulation could lead to novel treatments for pulmonary hypertension, offering hope for patients suffering from this debilitating condition.

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